retrospective validation
✓Validate methodology effectiveness using historical data without live deployment. Use when rich historical data exists (100+ instances), methodology targets observable patterns (error prevention, test strategy, performance optimization), pattern matching is feasible with clear detection rules, and live deployment has high friction (CI/CD integration effort, user study time, deployment risk). Enables 40-60% time reduction vs prospective validation, 60-80% cost reduction. Confidence calculation model provides statistical rigor. Validated in error recovery (1,336 errors, 23.7% prevention, 0.79 confidence).
Installation
SKILL.md
When you have 1,000 past errors, you don't need to wait for 1,000 future errors to prove your methodology works.
Result: Tool would have prevented 152 errors with 79% confidence.
| Time | Hours-days | Weeks-months | | Cost | Low (queries) | High (deployment) | | Risk | Zero | May introduce issues | | Confidence | 0.60-0.95 | 0.90-1.0 | | Data | Historical | New | | Scope | Full history | Limited window | | Bias | Hindsight | None |
Validate methodology effectiveness using historical data without live deployment. Use when rich historical data exists (100+ instances), methodology targets observable patterns (error prevention, test strategy, performance optimization), pattern matching is feasible with clear detection rules, and live deployment has high friction (CI/CD integration effort, user study time, deployment risk). Enables 40-60% time reduction vs prospective validation, 60-80% cost reduction. Confidence calculation model provides statistical rigor. Validated in error recovery (1,336 errors, 23.7% prevention, 0.79 confidence). Source: zpankz/mcp-skillset.
Facts (cite-ready)
Stable fields and commands for AI/search citations.
- Install command
npx skills add https://github.com/zpankz/mcp-skillset --skill retrospective validation- Source
- zpankz/mcp-skillset
- Category
- </>Dev Tools
- Verified
- ✓
- First Seen
- 2026-02-01
- Updated
- 2026-02-18
Quick answers
What is retrospective validation?
Validate methodology effectiveness using historical data without live deployment. Use when rich historical data exists (100+ instances), methodology targets observable patterns (error prevention, test strategy, performance optimization), pattern matching is feasible with clear detection rules, and live deployment has high friction (CI/CD integration effort, user study time, deployment risk). Enables 40-60% time reduction vs prospective validation, 60-80% cost reduction. Confidence calculation model provides statistical rigor. Validated in error recovery (1,336 errors, 23.7% prevention, 0.79 confidence). Source: zpankz/mcp-skillset.
How do I install retrospective validation?
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/zpankz/mcp-skillset --skill retrospective validation Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor
Where is the source repository?
https://github.com/zpankz/mcp-skillset
Details
- Category
- </>Dev Tools
- Source
- skills.sh
- First Seen
- 2026-02-01